1. Field of the Invention:
This invention relates generally to communications, more particularly to improving communication system performance through interference cancellation, and still more particularly to improved cancellation of multiple access interference in a code division multiple access communications environment.
2. Description of the Related Art:
Code Division Multiple Access (“CDMA”) provides an effective communications technique for several users to share a communications channel. Unfortunately, when the channel becomes overcrowded, the conventional CDMA receiver performs poorly and multiple access interference (“MAI”) can severely degrade performance. Although the optimal maximum likelihood receiver in this case is easy to describe, it is nearly impossible to implement.
Various conventional techniques examine interference cancellation at the symbol level. Symbol-level matched filters can provide a sufficient statistic for multi-user detection (“MUD”) in an additive white Gaussian noise channel. This well known result concludes that the optimal user bit estimation procedure can be written at the symbol level. Accordingly, these various conventional MUD approaches use symbol-level estimation and cancellation approaches. However, these symbol-level techniques are only approximations to the optimal estimator, and there is no guarantee that these symbol level approximations fully exploit the signal structure.
Additionally, conventional procedures can involve the following computationally expensive process for canceling interference: (1) interpolating the data for each source (base station) to the sampling lattice of the signature waveform (chip center), (2) computing the bit estimates for each user, (3) synthesizing the entire symbol's binary waveform and (4) interpolating the waveform of the whole symbol back to the sampling grid of the data to perform the cancellation.
Some sample-level approaches have been proposed. One example uses a continuous time (i.e., analog) maximum likelihood estimator (“MLE”) approach, which can be used as continuous decision feedback. This MLE approach can be purposed as a single-stage analog process using filters controlled by relative user power levels. Although relatively easy to implement, these approaches are not a good theoretical match to the interference cancellation problem. To remedy such shortcomings, linear minimum mean squared error (MMSE) techniques, such as those based on standard applications of the Kalman filter and other least-squares generalizations, could be used to reduce un-cancelled interference. These techniques fully couple the users (resulting in large matrix computations) and perform interference cancellations in the innovation term in the filter. Accordingly, they remain quite computationally expensive.
The above described techniques are also considered to be single stage algorithms. Multiple stage designs have also been considered. For example, in parallel with the development of symbol-level MMSE receivers, multi-stage parallel interference-cancellation (PIC) methods have been developed. In multi-stage PIC formulations, code matched filters are applied to the difference between the receive signal and the sum of the interference signals estimated from the previous stage. These multiple stage designs remain inadequate.
Each of the conventional techniques have been found to either be too complicated to embody in practical applications, or inadequate in terms of actual MAI cancellation in actual usage. Thus, techniques for canceling MAI that can be practically implemented while still providing effective cancellation remain needed.